ymoslem/whisper-medium-ga2en-v6.3.1-r
Automatic Speech Recognition
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Updated
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32
keyword
stringclasses 618
values | audio
audioduration (s) 0.97
1
| translation
stringclasses 537
values |
---|---|---|
abhaile | home |
|
abhaile | home |
|
abhaile | home |
|
abhainn | river |
|
abhainn | river |
|
abhainn | river |
|
abhainn | river |
|
abhainn | river |
|
abhainn | river |
|
ach | but |
|
ach | but |
|
ach | but |
|
ach | but |
|
ach | but |
|
ach | but |
|
ach | but |
|
ach | but |
|
ach | but |
|
ach | but |
|
ach | but |
|
ach | but |
|
ach | but |
|
ach | but |
|
ach | but |
|
ach | but |
|
ach | but |
|
ach | but |
|
ach | but |
|
ach | but |
|
ach | but |
|
ach | but |
|
ach | but |
|
ach | but |
|
ach | but |
|
ach | but |
|
ach | but |
|
ach | but |
|
ach | but |
|
ach | but |
|
ach | but |
|
ach | but |
|
ach | but |
|
ach | but |
|
ach | but |
|
ach | but |
|
ach | but |
|
ach | but |
|
ach | but |
|
ach | but |
|
ach | but |
|
ach | but |
|
ach | but |
|
ach | but |
|
ach | but |
|
ach | but |
|
ach | but |
|
ach | but |
|
ach | but |
|
ach | but |
|
ach | but |
|
ach | but |
|
ach | but |
|
ach | but |
|
ach | but |
|
ach | but |
|
ach | but |
|
ach | but |
|
ach | but |
|
ach | but |
|
ach | but |
|
ach | but |
|
ach | but |
|
ach | but |
|
ach | but |
|
ach | but |
|
ach | but |
|
ach | but |
|
ach | but |
|
ach | but |
|
ach | but |
|
achomhairc | appeals |
|
achomhairc | appeals |
|
achomhairc | appeals |
|
achomhairc | appeals |
|
achomhairc | appeals |
|
achomhairc | appeals |
|
achomhairc | appeals |
|
acht | act |
|
acht | act |
|
acht | act |
|
acht | act |
|
acht | act |
|
acht | act |
|
acht | act |
|
acht | act |
|
acht | act |
|
acht | act |
|
acmhainn | resource |
|
acmhainn | resource |
|
acmhainn | resource |
This is the Irish portion of the Spoken Words dataset (available at MLCommons/ml_spoken_words), with merged splits “train”, “validation”, and “test”, augmented with machine translation. The Irish sentences are automatically translated into English using Google Translation API. The dataset includes approximately 3 hours and 2 minutes of audio (03:02:02), spoken by multiple narrators.
Dataset({
features: ['keyword', 'audio', 'translation'],
num_rows: 10925
})
from datasets import load_dataset
dataset = load_dataset("SpokenWords-GA-EN-MTed",
split="train",
trust_remote_code=True
)
@inproceedings{mazumder2021multilingual,
title={Multilingual Spoken Words Corpus},
author={Mazumder, Mark and Chitlangia, Sharad and Banbury, Colby and Kang, Yiping and Ciro, Juan Manuel and Achorn, Keith and Galvez, Daniel and Sabini, Mark and Mattson, Peter and Kanter, David and others},
booktitle={Thirty-fifth Conference on Neural Information Processing Systems Datasets and Benchmarks Track (Round 2)},
year={2021}
}
@inproceedings{moslem2024leveraging,
title={Leveraging Synthetic Audio Data for End-to-End Low-Resource Speech Translation},
author={Moslem, Yasmin},
booktitle={Proceedings of the 2024 International Conference on Spoken Language Translation (IWSLT 2024)},
year={2024},
month={April}
}